Interesting perspective on the tradeoffs. I've been exploring the opposite end of this spectrum — I built a C#/WPF app that uses LLM APIs to generate fully native desktop applications from prompts at runtime. Think Canvas or Claude Code artifacts, but the output is compiled WPF with actual native controls, not a web view.
The app handles NuGet dependency resolution on the fly, catches runtime errors and feeds them back to the model for self-correction, and can export standalone executables (WPF for Windows, Avalonia for cross-platform). Everything is self-contained — users don't need to install any SDKs, IDEs, or toolchains.
I'm a teacher, not a startup founder, and I've been trying to market this commercially without much luck. Seriously considering open-sourcing the whole thing. Would love to hear what people here think about the native-vs-web approach for AI-generated applications.
The app handles NuGet dependency resolution on the fly, catches runtime errors and feeds them back to the model for self-correction, and can export standalone executables (WPF for Windows, Avalonia for cross-platform). Everything is self-contained — users don't need to install any SDKs, IDEs, or toolchains.
I'm a teacher, not a startup founder, and I've been trying to market this commercially without much luck. Seriously considering open-sourcing the whole thing. Would love to hear what people here think about the native-vs-web approach for AI-generated applications.
Happy to do a quick demo if anyone's curious.